Triple
T1788183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Métro Line 5 |
E39435
|
entity |
| Predicate | servesStation |
P839
|
FINISHED |
| Object |
Oberkampf
Oberkampf is a Paris Métro station in the 11th arrondissement, serving as an interchange between lines 5 and 9 near the lively Oberkampf district.
|
E199141
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Oberkampf | Statement: [Paris Métro Line 5, servesStation, Oberkampf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oberkampf Context triple: [Paris Métro Line 5, servesStation, Oberkampf]
-
A.
Choulex
Choulex is a small municipality in the canton of Geneva in southwestern Switzerland, known for its rural character and proximity to the city of Geneva.
-
B.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
-
C.
Larche
Larche is a small village in the French Alps near the Italian border, known as a gateway to the surrounding mountain passes and hiking routes.
-
D.
Pélissier
Pélissier is a French surname borne by various notable figures, including military leaders, athletes, and artists.
-
E.
Choully
Choully is a small wine-producing village in the commune of Satigny in the canton of Geneva, Switzerland.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Oberkampf Triple: [Paris Métro Line 5, servesStation, Oberkampf]
Generated description
Oberkampf is a Paris Métro station in the 11th arrondissement, serving as an interchange between lines 5 and 9 near the lively Oberkampf district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oberkampf Target entity description: Oberkampf is a Paris Métro station in the 11th arrondissement, serving as an interchange between lines 5 and 9 near the lively Oberkampf district.
-
A.
Choulex
Choulex is a small municipality in the canton of Geneva in southwestern Switzerland, known for its rural character and proximity to the city of Geneva.
-
B.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
-
C.
Larche
Larche is a small village in the French Alps near the Italian border, known as a gateway to the surrounding mountain passes and hiking routes.
-
D.
Pélissier
Pélissier is a French surname borne by various notable figures, including military leaders, athletes, and artists.
-
E.
Choully
Choully is a small wine-producing village in the commune of Satigny in the canton of Geneva, Switzerland.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa650fd3448190a6a2c979db982cae |
completed | March 6, 2026, 5:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada9a8a69c8190885bf06a06d3869f |
completed | March 8, 2026, 4:54 p.m. |
| NEDg | Description generation | batch_69adaab488ec81909a340aab4916b90f |
completed | March 8, 2026, 4:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adaf3cd23081909dd27c5de8e3f6d2 |
completed | March 8, 2026, 5:17 p.m. |
Created at: March 4, 2026, 7:32 p.m.